Learn to use R programming to apply linear models to analyze data in life sciences.

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

A focus on the techniques commonly used to perform statistical inference on high throughput data.

A focus on several techniques that are widely used in the analysis of high-dimensional data.

The structure, annotation, normalization, and interpretation of genome scale assays.

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale...

Traces Albert Einstein’s engagement with relativity, quantum mechanics, Nazism, nuclear weapons, philosophy, the arts, and...

Traces Albert Einstein’s engagement with relativity, quantum mechanics, Nazism, nuclear weapons, philosophy, the arts, and...

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.

Learn to process and convert raw data into formats needed for analysis. 

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

Explore the archaeology, history, art, and hieroglyphs surrounding the famous Egyptian Pyramids at Giza. Learn about Old Kingdom...

Discover the literature and heroes of ancient Greece through the Homeric Iliad and Odyssey, the tragedies of...

Explore and understand your own theories of learning and leadership. Gain the tools to imagine and build the future of learning.